The expression of microRNA (miRNA) is influenced by ongoing biological processes, including aging, and has begun to play a role in the measurement of neurodegenerative processes in central nervous system. The purpose of this study is to utilize machine learning approaches to determine whether miRNA can be utilized as a blood-based biomarker of cognitive aging. A random forest regression combining miRNA with biological (brain volume), clinical (comorbid conditions), and demographic variables in 115 typically aging older adults explained the greatest level of variance in cognitive performance compared to the other machine learning models explored. Three miRNA (miR-140-5p, miR-197-3p, and miR-501-3p) were top-ranked predictors of multiple cognitive outcomes (Fluid, Crystallized, and Overall Cognition) and past studies of these miRNA link them to cellular senescence, inflammatory signals for atherosclerotic formation, and potential development of neurodegenerative disorders (e.g., Alzheimer's disease). Several novel miRNAs were also linked to age and multiple cognitive functions, findings which together warrant further exploration linking these miRNAs to brain-derived metrics of neurodegeneration in typically aging older adults.

中文翻译：

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Micro RNA 预测健康老年人的认知表现

microRNA (miRNA) 的表达受到持续的生物过程（包括衰老）的影响，并已开始在中枢神经系统神经退行性过程的测量中发挥作用。本研究的目的是利用机器学习方法来确定 miRNA 是否可以用作认知衰老的血液生物标志物。对 115 名典型老龄化老年人进行的将 miRNA 与生物（脑容量）、临床（合并症）和人口统计学变量相结合的随机森林回归解释了与探索的其他机器学习模型相比认知表现的最大差异。三种 miRNA（miR-140-5p、miR-197-3p 和 miR-501-3p）是多种认知结果（流体认知、结晶认知和整体认知）的顶级预测因子，过去对这些 miRNA 的研究将它们与细胞衰老、动脉粥样硬化形成的炎症信号以及神经退行性疾病（例如阿尔茨海默病）的潜在发展。一些新的 miRNA 也与年龄和多种认知功能有关，这些发现共同值得进一步探索，将这些 miRNA 与典型老龄化老年人的脑源性神经退行性疾病指标联系起来。